Objective: We aimed to assess the prevalence of exposure by sector and the sectors of activity most exposed to each exposure, using routine occupational health data, and to quantify the risk of being exposed. Method: Occupational risk factors were assessed by workers followed by the Occupational Health Service of Cher, using self-reported questionnaires. The sectors of activity were grouped into seven sectors, and the risks were grouped into six occupational exposure groups. Comparisons were made using the Chi-squared test and Cramer’s V, and the odds ratios were calculated by using logistic regression. Results: We included 19,891 workers. The construction sector had the highest prevalence (p < 0.05 vs. all other sectors) of exposure to physical (76%) and biomechanical factors (82%), as well as chemical risks (75%). Human health and social work was the sector with the highest prevalence of exposure to biological factors (69%), psychosocial factors (90%), and atypical working hours (61%). With workers from administrative and support sectors as the reference, construction workers had more chance of declaring exposure to physical factors (OR = 3.28, 95%CI = 2.89 to 3.72), biomechanical factors (1.82, 1.58 to 2.09), and chemical agents (3.83, 3.38 to 4.33). Workers from the human health and social sectors had more chance of being exposed to biological agents (13.4, 11.9 to 15.2), atypical working hours (1.93, 1.75 to 2.14), and psychosocial factors (2.74, 2.38 to 3.16). Conclusion: Psychosocial risk factors were commonly reported in all sectors. Workers in the construction, human health, and social sectors seem to report more exposures than those in other sectors. The analysis of occupational exposures is a necessary basis to build an efficient preventive strategy for occupational health.

Background: Few studies have assessed work restrictions and unfitness to work simultaneously, particularly on large populations, and evidence on their main influencing factors remains limited. Objective: To assess prevalence and risk factors of work restrictions and unfitness to work. Method: We included all visits conducted in occupational health departments of the Cher, over two consecutive years. Visits had to have a conclusion: fitness to work, temporary work restrictions, permanent work restrictions, and unfitness to work. Mixed multinomial models with individual random effects were used. Results: Among the 71,848 occupational health visits, 62,436 had a conclusion. Most (90.6%, 95 CI 90.4 to 90.8%) were fit to work, 3.2% (3.1 to 3.3%) had temporary restrictions, 4.9% (4.7 to 5.1%) had permanent restrictions, and 1.3% (1.2 to 1.4%) were unfit to work. The risk of temporary restrictions was multiplied by 1.69 (1.16 to 2.48) in workers over 55 vs < 25 years old; by 1.74 (1.42 to 2.14) in workers with disabilities; by 1.30 (1.07 to 1.58) for workers with 10–20 vs < 5 years of seniority; and by 1.57 (1.22 to 2.01) in companies with 50–199 vs < 10 workers. The risk of permanent restrictions was multiplied by 2.24 (1.68 to 2.97) in workers over 55 yo; by 1.86 (1.57 to 2.21) in workers with disabilities; by 1.47 (1.05 to 2.06) for qualified workers; by 1.24 (1.05 to 1.46) for workers with 10–20 years of seniority; and by 1.30 (1.07 to 1.58) for workers in companies with 50–199 employees. The risk of unfitness to work decreased with increasing seniority in the company, while a significant interaction between sex and sector of activity was observed for temporary restrictions. Conclusion: Nearly one worker out of ten were unfit to work or had restrictions. The main risk factors for both unfit to work and restrictions were older age, women, and return-to-work visits; whereas lower seniority and smaller companies were risk factors for unfit to work, and longer seniority and bigger companies were risk factors for restrictions.

Background: To determine the impact of the Covid-19 pandemic on the number of occupational health consultations and to highlight influencing factors. Method: Retrospective observational study of consultations from an inter-company occupational health service. Data were retrieved during three consecutive years: 2019 (baseline), and 2020–2021. For comparisons purposes, we used the number of occupational health consultations per day and per full-time equivalent occupational healthcare worker (n consultations/d/FTE). Multivariate analysis was performed using logistic regression, for each lockdown vs the same period one year before. Results: A total of 103,351 consultations were included. The number of consultations decreased by 14.3% in 2020 compared to 2019 but increased by 33.7% in 2021 compared to 2020. There were 4.9 consultations/d/FTE, 4.69 to 5.12 in 2019; 4.07, 3.81 to 4.34 in 2020; and 5.35, 5.16 to 5.55 in 2021. The first lockdown had a massive impact on the number of consultations, whereas the activity returned to normal from August 2020 with an increase in 2021. Age was associated with a decrease in the propension of consulting for the three lockdown periods (p < 0.001). The proportion of consultations for return-to-work was multiplied by 2.44 (2.02 to 2.95, p < 0.001) during the first lockdown, associated with a reduced risk of being declared unfit to work (OR = 0.48, 95 CI 0.27 to 0.84, p = 0.010). Conclusion: The Covid-19 pandemic had a huge impact on the medical activity of occupational health departments, with a massive decrease in 2020 followed by an increase in 2021 compared to 2019.

Les services de santé au travail ont un rôle majeur dans le maintien dans l'emploi. Toutefois, il n'existe aucun travail de niveau international analysant les données massives de santé au travail pour prévenir la désinsertion professionnelle. L'Article 1 est une analyse longitudinale de l'évolution des flux de 112 000 visites en santé au travail au cours de la pandémie Covid, et représente une première approche macroscopique des salariés les plus à risque de consulter en santé au travail. L'Article 2 démontre, via l'analyse de 20 000 salariés, les risques professionnels de différents secteurs d'activité - préalable indispensable à la prévention de la désinsertion professionnelle. L'Article 3 identifie les facteurs de risques d'aptitude avec réserves temporaires, définitives, ou d'inaptitude, sur 72 000 salariés. Enfin, l'Article 4 évalue un score de désinsertion professionnelle, via une analyse transversale de 8000 salariés. Les travaux futurs devront analyser l'évolution longitudinal de ce risque de désinsertion professionnelle, dans le but d'identifier les facteurs prédictifs d'une inaptitude totale et définitive à tout poste, et donc d'une sortie prématurée de l'emploi.